{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Demographic Prisoner's Dilemma\n",
    "\n",
    "The Demographic Prisoner's Dilemma is a family of variants on the classic two-player [Prisoner's Dilemma](https://en.wikipedia.org/wiki/Prisoner's_dilemma), first developed by [Joshua Epstein](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.8.8629&rep=rep1&type=pdf). The model consists of agents, each with a strategy of either Cooperate or Defect. Each agent's payoff is based on its strategy and the strategies of its spatial neighbors. After each step of the model, the agents adopt the strategy of their neighbor with the highest total score. \n",
    "\n",
    "The specific variant presented here is adapted from the [Evolutionary Prisoner's Dilemma](http://ccl.northwestern.edu/netlogo/models/PDBasicEvolutionary) model included with NetLogo. Its payoff table is a slight variant of the traditional PD payoff table:\n",
    "\n",
    "<table>\n",
    "    <tr><td></td><td>**Cooperate**</td><td>**Defect**</td></tr>\n",
    "    <tr><td>**Cooperate**</td><td>1, 1</td><td>0, *D*</td></tr>\n",
    "    <tr><td>**Defect**</td><td>*D*, 0</td><td>0, 0</td></tr>\n",
    "</table>\n",
    "\n",
    "Where *D* is the defection bonus, generally set higher than 1. In these runs, the defection bonus is set to $D=1.6$.\n",
    "\n",
    "The Demographic Prisoner's Dilemma demonstrates how simple rules can lead to the emergence of widespread cooperation, despite the Defection strategy dominiating each individual interaction game. However, it is also interesting for another reason: it is known to be sensitive to the activation regime employed in it.\n",
    "\n",
    "Below, we demonstrate this by instantiating the same model (with the same random seed) three times, with three different activation regimes: \n",
    "\n",
    "* Sequential activation, where agents are activated in the order they were added to the model;\n",
    "* Random activation, where they are activated in random order every step;\n",
    "* Simultaneous activation, simulating them all being activated simultaneously.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pd_grid.model import PdGrid\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Helper functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "bwr = plt.get_cmap(\"bwr\")\n",
    "\n",
    "def draw_grid(model, ax=None):\n",
    "    '''\n",
    "    Draw the current state of the grid, with Defecting agents in red\n",
    "    and Cooperating agents in blue.\n",
    "    '''\n",
    "    if not ax:\n",
    "        fig, ax = plt.subplots(figsize=(6,6))\n",
    "    grid = np.zeros((model.grid.width, model.grid.height))\n",
    "    for agent, x, y in model.grid.coord_iter():\n",
    "        if agent.move == \"D\":\n",
    "            grid[y][x] = 1\n",
    "        else:\n",
    "            grid[y][x] = 0\n",
    "    ax.pcolormesh(grid, cmap=bwr, vmin=0, vmax=1)\n",
    "    ax.axis('off')\n",
    "    ax.set_title(\"Steps: {}\".format(model.schedule.steps))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run_model(model):\n",
    "    '''\n",
    "    Run an experiment with a given model, and plot the results.\n",
    "    '''\n",
    "    fig = plt.figure(figsize=(12,8))\n",
    "    \n",
    "    ax1 = fig.add_subplot(231)\n",
    "    ax2 = fig.add_subplot(232)\n",
    "    ax3 = fig.add_subplot(233)\n",
    "    ax4 = fig.add_subplot(212)\n",
    "    \n",
    "    draw_grid(model, ax1)\n",
    "    model.run(10)\n",
    "    draw_grid(model, ax2)\n",
    "    model.run(10)\n",
    "    draw_grid(model, ax3)\n",
    "    model.datacollector.get_model_vars_dataframe().plot(ax=ax4)\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set the random seed\n",
    "seed = 21"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sequential Activation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = PdGrid(50, 50, \"Sequential\", seed=seed)\n",
    "run_model(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Activation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = PdGrid(50, 50, \"Random\", seed=seed)\n",
    "run_model(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Simultaneous Activation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = PdGrid(50, 50, \"Simultaneous\", seed=seed)\n",
    "run_model(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:mesa]",
   "language": "python",
   "name": "conda-env-mesa-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
